DBMS > Amazon DynamoDB vs. Microsoft Access vs. Titan vs. Vitess

System Properties Comparison Amazon DynamoDB vs. Microsoft Access vs. Titan vs. Vitess

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Titan is a Graph DBMS optimized for distributed clusters.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Key-value store

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

aws.amazon.com/dynamodb

www.microsoft.com/en-us/microsoft-365/access

github.com/thinkaurelius/titan

vitess.io

Technical documentation

docs.aws.amazon.com/dynamodb

developer.microsoft.com/en-us/access

github.com/thinkaurelius/titan/wiki

vitess.io/docs

Developer

Amazon

Microsoft

Aurelius, owned by DataStax

The Linux Foundation, PlanetScale

Initial release

2012

1992

2012

2013

Current release

1902 (16.0.11328.20222), March 2019

15.0.2, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Bundled with Microsoft Office

Open Source

Apache license, version 2.0

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Clojure
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

Relationships in graph

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

but no files for transaction logging

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

a simple user-level security was built in till version Access 2003

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

no user groups or roles

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